Muhammad Naeem

Cognitive Neuroscience · with Brunner · 2006

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 12 citations into it; #8,472 of 10,852 by trust here, #8,619 by citations
• Signal Processing — 6 citations into it; #6,443 of 7,572 by trust here, #5,570 by citations

Whom Muhammad Naeem trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Herbert Ramoser
2. Arnaud Delorme
3. Wei Lu
4. Gert Pfurtscheller
5. Christoph Guger
6. Scott Makeig
7. Benjamin Blankertz
8. Guido Dornhege
9. Steven Lemm
10. Bernhard Graimann

Who trusts Muhammad Naeem overall

1. Fabien Lotte
2. Christian Andreas Kothe
3. Florian Yger
4. Turky Nayef Alotaiby
5. Mahnaz Arvaneh
6. Cuntai Guan
7. Scott Makeig
8. Maxime Bérar
9. Fathi E. Abd El-Samie

Papers from Muhammad Naeem's perspective

Ordered by how strongly the researchers Muhammad Naeem trusts endorse each paper. Same corpus, a different order for every researcher.

1. Optimal spatial filtering of single trial EEG during imagined hand movement. (IEEE transactions on rehabilitation engineering)
2. Real-time EEG analysis with subject-specific spatial patterns for a brain-computer interface (BCI). (IEEE transactions on rehabilitation engineering)
3. Spatio-spectral filters for improving the classification of single trial EEG (IEEE Transactions on Biomedical Engineering)
4. Boosting bit rates in noninvasive EEG single-trial classifications by feature combination and multiclass paradigms (IEEE Transactions on Biomedical Engineering)
5. Independent component analysis: algorithms and applications
6. Mining event-related brain dynamics. (Trends in Cognitive Sciences)
7. Independent Component Analysis as a Tool to Eliminate Artifacts in EEG: A Quantitative Study (Journal of clinical neurophysiology)
8. Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks (NeuroImage)
9. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. (Journal of Neuroscience Methods)
10. A blind source separation technique using second-order statistics

Their papers

• Seperability of four-class motor imagery data using independent components analysis (2006) — 303 citations